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KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences

dc.contributor.authorSchultheiss, Sebastian
dc.contributor.authorBusch, Wolfgang
dc.contributor.authorLohmann, Jan U.
dc.contributor.authorKohlbacher, Oliver
dc.contributor.authorRätsch, Gunnar
dc.contributor.editorBeyer, Andreas
dc.contributor.editorSchroeder, Michael
dc.date.accessioned2019-04-03T12:07:32Z
dc.date.available2019-04-03T12:07:32Z
dc.date.issued2008
dc.description.abstractMotivation: Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor binding sites in promoter regions of potential transcription factor target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling or heuristics for extending seed oligos. Such algorithms succeed in identifying single, relatively well conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites as those often found in cis-regulatory modules. Results: We propose a new algorithm that combines the benefits of existing motif finding with the ones of Support Vector Machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana we were able to show that the newly developed strat- egy significantly improves the recognition of transcription factor targets. Availability: The PYTHON source code (open source–licensed under GPL), the data for the experiments and a web-service are available at http://www.fml.mpg. de/raetsch/projects/kirmes. Contact: sebi@tuebingen.mpg.deen
dc.identifier.isbn978-3-88579-226-0
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/21212
dc.language.isoen
dc.publisherGesellschaft für Informatik e. V.
dc.relation.ispartofGerman Conference on Bioinformatics
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-136
dc.titleKIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequencesen
dc.typeText/Conference Paper
gi.citation.endPage167
gi.citation.publisherPlaceBonn
gi.citation.startPage158
gi.conference.date09.-12.09.2008
gi.conference.locationDresden
gi.conference.sessiontitleRegular Research Papers

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